update meta files

Author: paul-buerkner

DESCRIPTION

@@ -1,17 +1,18 @@
 Package: brms
 Type: Package
 Title: Bayesian Regression Models using Stan
-Version: 0.4.1.9001
-Date: 2015-09-03
+Version: 0.5.0
+Date: 2015-09-11
 Authors@R: person("Paul-Christian", "Buerkner", email = "[email protected]",
   role = c("aut", "cre"))
 Depends: R (>= 3.1.0), rstan (>= 2.7.0), ggplot2 (>= 1.0.1) 
 Imports: loo (>= 0.1.2), shinystan (>= 2.0.0), gridExtra (>= 2.0.0), abind, 
   methods, stats, parallel, grDevices, grid
-Suggests: testthat (>= 0.9.1)
+Suggests: testthat (>= 0.9.1), R.rsp
 Description: Fit Bayesian generalized linear mixed models using Stan for full Bayesian inference.
 LazyData: true
 NeedsCompilation: no
 License: GPL (>= 3)
 URL: http://github.com/paul-buerkner/brms
 BugReports: http://github.com/paul-buerkner/brms/issues
+VignetteBuilder: R.rsp

NAMESPACE

@@ -31,6 +31,7 @@ S3method(residuals,brmsfit)
 S3method(stancode,brmsfit)
 S3method(standata,brmsfit)
 S3method(summary,brmsfit)
+S3method(vcov,brmsfit)
 export(LOO)
 export(VarCorr)
 export(WAIC)

News.md

@@ -3,20 +3,21 @@ title: "News"
 output: html_document
 ---
 
-# under development
+# brms 0.5.0
 ----------------------------------------------------------------
 
 ## new features
-* compute the Watanabe-Akaike information criterion (WAIC) and the leave-one-out cross-validation (LOO) using the loo package.
+* compute the Watanabe-Akaike information criterion (WAIC) and leave-one-out cross-validation (LOO) using the loo package.
 * provide an interface to shinystan with S3 method 'launch_shiny'.
 * new functions 'get\_prior' and 'set\_prior' to make prior specifications easier.
-* log-likelihood values and posterior predictive samples can now be calculated after the model has been fitted. 
+* log-likelihood values and posterior predictive samples can now be calculated within R after the model has been fitted. 
 * make predictions based on new data using S3 method 'predict'.
-* allow for customized covariance structures of grouping factors with multiple random effects
+* allow for customized covariance structures of grouping factors with multiple random effects.
 * new S3 methods 'fitted' and 'residuals' to compute fitted values and residuals, respectively.
 
 ## other changes
-* arguments WAIC and predict are removed from function brm as they are no longer necessary.
+* arguments 'WAIC' and 'predict' are removed from function 'brm' as they are no longer necessary.
+* new argument 'cluster_type' in function 'brm' allowing to choose the cluster type created by the parallel package
 * remove chains that fail to initialize while sampling in parallel leaving the other chains untouched.
 * redesign trace and density plots to be faster and more stable.
 * S3 method 'VarCorr' now always returns covariance matrices regardless of whether correlations were estimated.

README.md

@@ -83,7 +83,7 @@ methods(class = "brmsfit")
 #>  [9] ngrps             nobs              parnames          plot             
 #> [13] posterior_samples predict           print             prior_samples    
 #> [17] ranef             residuals         stancode          standata         
-#> [21] summary           VarCorr           WAIC             
+#> [21] summary           VarCorr           vcov              WAIC             
 #> see '?methods' for accessing help and source code
 ```
 

cran-comments.md

@@ -1,10 +1,8 @@
-This is an update to fix a critical bug.
-
 ## Test environments
-* local Windows 8.1 install, R 3.2.0, R 3.3.0
+* local Windows 8.1 install, R 3.2.2, R 3.3.0
 * win-builder (devel and release)
-* ubuntu 12.04, R 3.2.0
-* local OS X install, R 3.2.0
+* ubuntu 12.04, R 3.2.2
+* local OS X install, R 3.2.2
 
 ## R CMD check results
 There were no ERRORs, WARNINGs or NOTEs.